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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
probe_id: string
kind: string
notebook: string
drive_id: string
dataset: string
num_res_blocks: int64
seed: int64
batch_size: int64
weight_decay: double
label_smoothing: double
ckpt_repo: string
data_repo: string
holdout_idx: int64
checkpoints: struct<svez_ep01: string, zreo_ep10: string>
child 0, svez_ep01: string
child 1, zreo_ep10: string
config: struct<etas: list<item: double>, K_steps: int64, n_seeds: int64, val_batches: int64, sigma: double, (... 100 chars omitted)
child 0, etas: list<item: double>
child 0, item: double
child 1, K_steps: int64
child 2, n_seeds: int64
child 3, val_batches: int64
child 4, sigma: double
child 5, tau: double
child 6, measure_bf16: bool
child 7, measure_ascent: bool
child 8, eta_max_smith: double
child 9, tail_fraction: double
env: struct<torch: string, gpu: string, timestamp: string>
child 0, torch: string
child 1, gpu: string
child 2, timestamp: string
results: list<item: struct<label: string, rows: list<item: struct<eta: double, d: double, d_sd: double, ctl: (... 179 chars omitted)
child 0, item: struct<label: string, rows: list<item: struct<eta: double, d: double, d_sd: double, ctl: double, ctl (... 167 chars omitted)
child 0, label: string
child 1, rows: list<item: struct<eta: double, d: double, d_sd: double, ctl: double, ctl_sd: double, asc: double, bf (... 56 chars omitted)
child 0, item: struct<eta: double, d: double, d_sd: double, ctl: double, ctl_sd: double, asc: double, bf16: double, (... 44 chars omitted)
child 0, eta: double
child 1, d: double
child 2, d_sd: double
child 3, ctl: double
child 4, ctl_sd: double
child 5, asc: double
child 6, bf16: double
child 7, frac: double
child 8, relmv: double
child 9, all_neg: bool
child 2, floor: double
child 3, floor_bf16: double
child 4, numeric: double
child 5, useful: double
child 6, n_pos: int64
eta_min_proposed: double
k_steps: int64
lr_grid: list<item: double>
child 0, item: double
n_seeds: int64
test: string
lr_floor: struct<0: double, 1: double, 2: double, 3: double, 4: double, 5: double, 6: null, 7: null, 8: null, (... 18 chars omitted)
child 0, 0: double
child 1, 1: double
child 2, 2: double
child 3, 3: double
child 4, 4: double
child 5, 5: double
child 6, 6: null
child 7, 7: null
child 8, 8: null
child 9, 9: null
child 10, 10: null
alpha: double
probe_points: list<item: int64>
child 0, item: int64
eval_batches: int64
ckpt_hf_dir: string
to
{'probe_id': Value('string'), 'dataset': Value('string'), 'num_res_blocks': Value('int64'), 'seed': Value('int64'), 'ckpt_hf_dir': Value('string'), 'probe_points': List(Value('int64')), 'lr_grid': List(Value('float64')), 'k_steps': Value('int64'), 'n_seeds': Value('int64'), 'eval_batches': Value('int64'), 'alpha': Value('float64'), 'weight_decay': Value('float64'), 'batch_size': Value('int64'), 'test': Value('string'), 'lr_floor': {'0': Value('float64'), '1': Value('float64'), '2': Value('float64'), '3': Value('float64'), '4': Value('float64'), '5': Value('float64'), '6': Value('null'), '7': Value('null'), '8': Value('null'), '9': Value('null'), '10': Value('null')}, 'results': {'0': {'L_pre': Value('float64'), 'delta': {'1e-07': List(Value('float64')), '3e-07': List(Value('float64')), '1e-06': List(Value('float64')), '3e-06': List(Value('float64')), '1e-05': List(Value('float64')), '3e-05': List(Value('float64')), '0.0001': List(Value('float64')), '0.0': List(Value('float64'))}, 'welch': {'1e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '0.0001': {'t': Value
...
1': List(Value('float64')), '0.0': List(Value('float64'))}, 'welch': {'1e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '0.0001': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}}}, '10': {'L_pre': Value('float64'), 'delta': {'1e-07': List(Value('float64')), '3e-07': List(Value('float64')), '1e-06': List(Value('float64')), '3e-06': List(Value('float64')), '1e-05': List(Value('float64')), '3e-05': List(Value('float64')), '0.0001': List(Value('float64')), '0.0': List(Value('float64'))}, 'welch': {'1e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '0.0001': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}}}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
probe_id: string
kind: string
notebook: string
drive_id: string
dataset: string
num_res_blocks: int64
seed: int64
batch_size: int64
weight_decay: double
label_smoothing: double
ckpt_repo: string
data_repo: string
holdout_idx: int64
checkpoints: struct<svez_ep01: string, zreo_ep10: string>
child 0, svez_ep01: string
child 1, zreo_ep10: string
config: struct<etas: list<item: double>, K_steps: int64, n_seeds: int64, val_batches: int64, sigma: double, (... 100 chars omitted)
child 0, etas: list<item: double>
child 0, item: double
child 1, K_steps: int64
child 2, n_seeds: int64
child 3, val_batches: int64
child 4, sigma: double
child 5, tau: double
child 6, measure_bf16: bool
child 7, measure_ascent: bool
child 8, eta_max_smith: double
child 9, tail_fraction: double
env: struct<torch: string, gpu: string, timestamp: string>
child 0, torch: string
child 1, gpu: string
child 2, timestamp: string
results: list<item: struct<label: string, rows: list<item: struct<eta: double, d: double, d_sd: double, ctl: (... 179 chars omitted)
child 0, item: struct<label: string, rows: list<item: struct<eta: double, d: double, d_sd: double, ctl: double, ctl (... 167 chars omitted)
child 0, label: string
child 1, rows: list<item: struct<eta: double, d: double, d_sd: double, ctl: double, ctl_sd: double, asc: double, bf (... 56 chars omitted)
child 0, item: struct<eta: double, d: double, d_sd: double, ctl: double, ctl_sd: double, asc: double, bf16: double, (... 44 chars omitted)
child 0, eta: double
child 1, d: double
child 2, d_sd: double
child 3, ctl: double
child 4, ctl_sd: double
child 5, asc: double
child 6, bf16: double
child 7, frac: double
child 8, relmv: double
child 9, all_neg: bool
child 2, floor: double
child 3, floor_bf16: double
child 4, numeric: double
child 5, useful: double
child 6, n_pos: int64
eta_min_proposed: double
k_steps: int64
lr_grid: list<item: double>
child 0, item: double
n_seeds: int64
test: string
lr_floor: struct<0: double, 1: double, 2: double, 3: double, 4: double, 5: double, 6: null, 7: null, 8: null, (... 18 chars omitted)
child 0, 0: double
child 1, 1: double
child 2, 2: double
child 3, 3: double
child 4, 4: double
child 5, 5: double
child 6, 6: null
child 7, 7: null
child 8, 8: null
child 9, 9: null
child 10, 10: null
alpha: double
probe_points: list<item: int64>
child 0, item: int64
eval_batches: int64
ckpt_hf_dir: string
to
{'probe_id': Value('string'), 'dataset': Value('string'), 'num_res_blocks': Value('int64'), 'seed': Value('int64'), 'ckpt_hf_dir': Value('string'), 'probe_points': List(Value('int64')), 'lr_grid': List(Value('float64')), 'k_steps': Value('int64'), 'n_seeds': Value('int64'), 'eval_batches': Value('int64'), 'alpha': Value('float64'), 'weight_decay': Value('float64'), 'batch_size': Value('int64'), 'test': Value('string'), 'lr_floor': {'0': Value('float64'), '1': Value('float64'), '2': Value('float64'), '3': Value('float64'), '4': Value('float64'), '5': Value('float64'), '6': Value('null'), '7': Value('null'), '8': Value('null'), '9': Value('null'), '10': Value('null')}, 'results': {'0': {'L_pre': Value('float64'), 'delta': {'1e-07': List(Value('float64')), '3e-07': List(Value('float64')), '1e-06': List(Value('float64')), '3e-06': List(Value('float64')), '1e-05': List(Value('float64')), '3e-05': List(Value('float64')), '0.0001': List(Value('float64')), '0.0': List(Value('float64'))}, 'welch': {'1e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '0.0001': {'t': Value
...
1': List(Value('float64')), '0.0': List(Value('float64'))}, 'welch': {'1e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '0.0001': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}}}, '10': {'L_pre': Value('float64'), 'delta': {'1e-07': List(Value('float64')), '3e-07': List(Value('float64')), '1e-06': List(Value('float64')), '3e-06': List(Value('float64')), '1e-05': List(Value('float64')), '3e-05': List(Value('float64')), '0.0001': List(Value('float64')), '0.0': List(Value('float64'))}, 'welch': {'1e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-07': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-06': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '1e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '3e-05': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}, '0.0001': {'t': Value('float64'), 'p': Value('float64'), 'sig': Value('bool')}}}}}
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